System and method for determining a driver in a telematic application

ABSTRACT

A system and method for a telematic application on a mobile electronic device that can include detecting, in the telematic application, vehicular travel; collecting, in the telematic application, driver status identification data; determining a driver status based on the driver status identification data; recording the driver status; and recording telematic data based on the driver status.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.15/401,761, filed 9 Jan. 2017, which is a continuation-in-part of priorU.S. application Ser. No. 14/206,721, filed on 12 Mar. 2014, whichclaims the benefit of U.S. Provisional Application Ser. No. 61/778,209,filed on 12 Mar. 2013, which are both incorporated in their entirety bythis reference.

This application is also a continuation-in-part of prior U.S.application Ser. No. 15/243,513, filed on 22 Aug. 2016, which claims thebenefit of U.S. Provisional Application Ser. No. 62/207,461, filed on 20Aug. 2015, which are both incorporated in their entirety by thisreference.

TECHNICAL FIELD

This invention relates generally to the vehicle telematics field, andmore specifically to a new and useful system and method for determininga driver status in a telematic application in the vehicle telematicsfield.

BACKGROUND

Vehicle telematic devices monitor the location, movements, status, andbehavior of a vehicle. Such devices commonly use GPS receivers and anelectronic device to transmit the collected data. The vehicle telematicdevices may additionally include capabilities to interface with signalsfrom the car. Such devices are often installed in the car or vehicle.Mobile phones contain similar sensing capabilities as telematic devicesinstalled on the device and are owned by more people. However, mobilephones are often carried with a person, and vehicle travel experiencedby a device may be when the owner is driving, a passenger in a car, apassenger on public transportation, or during any state of travel. Thus,there is a need in the vehicle telematic field to create a new anduseful system and method for determining a driver status in a telematicapplication. This invention provides such a new and useful system andmethod.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 is a flowchart representation of a method of a preferredembodiment;

FIG. 2 is a schematic representation of detecting a beacon signal anddetermining position of a preferred embodiment;

FIG. 3 is a schematic representation of collecting a driving-patternsignature of a preferred embodiment;

FIG. 4 is a schematic representation of collecting an audio signature ofa preferred embodiment;

FIG. 5 is a schematic representation of detecting a vehicle identifyingsignal of a preferred embodiment;

FIG. 6 is a schematic representation of a system of a preferredembodiment; and

FIGS. 7A-7B are schematic representations of variations of elements ofthe method performed by a computing system.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

The following description of the preferred embodiments of the inventionis not intended to limit the invention to these preferred embodiments,but rather to enable any person skilled in the art to make and use thisinvention.

1. Methods for Determining a Driver in a Telematic Application

As shown in FIG. 1, a method for determining a driver status in atelematic application can include providing a telematic applicationS110, detecting vehicular travel S120, collecting driver statusidentification (DSI) data S130, determining a driver status S140, andrecording the driver status S150.

The method functions to determine when a user of a device is driving ornot driving. Knowing when a user is driving a vehicle or not can enabletelematic data to be collected by a user device (e.g., mobile electronicdevice) and associated with the appropriate person. In one exemplaryimplementation, collecting telematic data and the driver associated withthat data can be used in evaluating the risk of insuring a driver. Asone application, a remote software platform can host and manage drivingdata for a plurality of different drivers. The drivers may each have atelematics application installed on a personal, mobile computing devicethat automatically detects when the user is driving and collectstelematics data. Thus, the telematics application can be programmed incomputer code to execute one or more blocks of the method 100 describedherein, upon download, installation, and/or running of the telematicsapplication on the mobile computing devices of the drivers. Theinstances of the telematics application running at mobile computingdevices can coordinate one or more of: data collection, data transfer,data analysis, and feedback to the drivers or other entities (e.g.,insurance providers) according to the method 100 described herein.

As driver determination is automatically performed by instances of theapplication in communication with computing systems programmed to beoperable for analysis of driver and driving data, driving data can becollected in any vehicle and used to identify the driver(s) of thevehicle(s). Additionally or alternatively, telematics data can becollected in situations when the user is a passenger, and data isacquired by way of a telematic application executing at the computingdevice of the passenger. In insurance use case passenger telematics datacould be mapped to social connections of the user or used in anysuitable manner. The method may alternatively be used in any suitableapplication. The method may be implemented through various techniquesand combinations of techniques for collecting driver status signals anddetermining driver status. Such variations may rely on car-baseddevices, audio detection, and/or physical event detection.

Step S110, which includes providing a telematic application, functionsto enable a telematic logging software to be operable on a mobileelectronic device. The telematic application is preferably operable on amobile electronic device associated with a single entity. The methodmay, in some variations, create an association between the applicationinstance and a particular user account. In this way, driving telematicdata may be logged for a particular user. In another variation, theidentity of a car may be identified by the application, and thetelematic data and/or driver status may be logged for a particularvehicle. The user device is preferably a mobile phone, but mayalternatively be a wearable computing device, a tablet, a personaldata-logging device, or any suitable device.

The method can include coupling the user device (e.g., mobile electronicdevice) to a vehicle. The user device can remain coupled to the vehiclethroughout (or substantially throughout) a time period (e.g., throughouta driving session during which the vehicle is driven), can be coupled toand decoupled from the vehicle one or more times throughout the timeperiod, and/or can be coupled to the vehicle at any other suitable time.

The user device is preferably movably coupled to the vehicle. In a firstembodiment, the user device is movably coupled to the vehicle through auser (e.g., vehicle driver, vehicle passenger). In a first variation ofthis embodiment, the user device is retained by an article of clothingof the user (e.g., in a pocket; by a belt of waistband, such as in aholster connected to the belt or waistband; etc.). In a second variationof this embodiment, the user device is held by the user (e.g., in theuser's hand hand; between two body parts, such as between the user'sface and shoulder or between the user's arm and torso; etc.). In a thirdvariation of this embodiment, the user device rests (e.g., is retainedby gravity) on the user (e.g., on the user's lap). In a third variationof this embodiment, the user device is worn by the user (e.g., in asleeve, in the form factor of a limb-coupled mobile device, etc.).

In a second embodiment, the user device is movably coupled to thevehicle by a mount (e.g., mount attached to the vehicle). The mount canbe removably or irremovably attached (e.g., by a suction element,magnet, adhesive, mechanical fastener, clip, friction fit, etc.) to thevehicle (e.g., windshield, dashboard, vent cover, etc.), be of unitaryconstruction with the vehicle, or be otherwise suitably coupled to thevehicle. The mount can be removably or irremovably attached (e.g., by asuction element, magnet, adhesive, mechanical fastener, clip, frictionfit, etc.) to the user device or be otherwise suitably coupled to theuser device. The mount can be a rotatable mount operable to rotatablycouple the user device to the vehicle (e.g., allowing rotation of theuser device about one or more axes with respect to the vehicle). In athird embodiment, the user device rests (e.g., is retained by gravity)on the vehicle (e.g., on a substantially horizontal surface, in a cupholder, etc.). Alternatively, the user device can be immovably coupledto the vehicle (e.g., rigidly connected to the vehicle), or coupled tothe vehicle in any other suitable way.

The telematic application is preferably an application downloaded andinstalled on the device, but the application may alternatively beembedded in the device, operated through a browser, or installed on thedevice in any suitable manner. The telematic application may at leastpartially operate in the background. The background operation of thetelematic application preferably functions to detect and record vehicledata. The telematic application may additionally interface with servicesprovided by the operating system or other frameworks to efficientlymonitor and collect telematic data.

The telematic application can preferably provide data on location androutes, movements, driving patterns (e.g., steering and brakingcharacteristics), and other properties. The telematic applicationpreferably uses services and sensors accessible on the mobile devicesuch as GPS sensors, location services, accelerometers, gyroscopes,presence sensors, and/or any suitable input signal accessible by theapplication. The telematic data may be used with outside data sources tocorrelate additional properties of driving. The additional properties ofdriving may be generated on the telematic application or alternativelyby a remote telematic data platform. The telematic applicationpreferably communicates data to the remote telematic data platform forhosting, processing, and sharing. Additionally, properties of drivingmay include traffic level of travel, speed relative to flow of traffic,observance of traffic laws (e.g., does the driver stop at stop signs),driving weather, and/or other suitable driving properties.

Step S120, which includes detecting vehicular travel, functions tomeasure when the mobile electronic device experiences vehicular travel.Vehicular travel is preferably characterized by travel patterns expectedfrom a powered vehicle such as a car, truck, train, bus, motorcycle,plane, helicopter, boat, jet ski, or any suitable vehicle. For cars andother road-based vehicles, vehicular travel may be characterized bytraveling within particular speed ranges and/or following a travel routeconsistent with roads and traffic patterns. For example, motion datathat indicates that a mobile electronic device is currently travelingsubstantially along a highway route at 60 mph would preferably be astrong indicator that the mobile electronic device is experiencingvehicular travel. The telematic application preferably detects vehiculartravel for logging telematic data as described above, and the telematicapplication may use such data in identifying vehicular travel patternsevident in the telematic data. The telematic application mayadditionally selectively enable or disable logging. Selectively enablingand disabling logging may be based in part on if the device isexperiencing vehicular travel. Additionally, the detection of vehiculartravel may activate or initiate the collection of driver status signalsand the determination of driver status. For example, a telematicapplication may periodically monitor the location of a device. When theapplication detects the devices is traveling at car-like speeds, thetelematic application may detect if the device is in a driver mode.Alternatively, determining that the driver status is in a driving modemay activate or initiate the detection of vehicular travel. For example,in a variation where the telematic application detects a beacon signal,the presence of the beacon signal may initiate detection of vehiculartravel. S120 is preferably performed while the user device is coupled tothe vehicle (e.g., movably coupled during the time period), but canadditionally or alternatively be performed at any other suitable time.

Step S130, which includes collecting driver status identification (DSI)data, functions to collect data to allow identification of a driverstatus for a user of the telematic application. The user is preferablythe primary user of the mobile electronic device running the telematicapplication, but may additionally or alternatively be any other user.DSI data preferably includes any data that could be used to identify thedriver status of the user and/or the driver status of a vehicle the useris traveling in; e.g., whether the user is driving or not, how the useris driving/being driven, and what vehicle the user is driving/beingdriven in. DSI data is preferably collected from sensors of the mobileelectronic device, but may additionally or alternatively be collectedfrom any suitable source; e.g., sensors integrated into or external tothe vehicle. DSI data is preferably collected by a telematic applicationrunning on the mobile electronic device, but may additionally oralternatively be collected by any suitable device. Collecting DSI dataS130 may include collecting device position data S131, collecting devicemotion data S132, collecting vehicle motion data S133, collectingvehicle identifying data S134, collecting vehicle use data S135, and/orcollecting device use data S136. S130 is preferably performed while theuser device is coupled to the vehicle (e.g., moveably coupled during thetime period), but can additionally or alternatively be performed at anyother suitable time.

Collecting DSI data S130 preferably includes collecting DSI dataselectively. For example, DSI data may only be collected while vehicularmotion is detected. As another example, the types of DSI data collectedmay change based on the status of the mobile electronic device, avehicle and/or the user; GPS data from the mobile electronic device mayonly be collected when the mobile electronic device is connected to anexternal power source, while accelerometer data may be collected at alltimes. The status of the mobile electronic device, a vehicle, and/or theuser may additionally or alternatively modify the frequency or otherparameters of DSI data collection. For example, GPS data from the mobileelectronic device may be collected once every ten seconds when themobile electronic device is not connected to an external power sourceand continuously when the mobile electronic device is connected to anexternal power source.

Step S131, which includes collecting device position data, functions tocollect data on the position of the mobile electronic device. Collectingdevice position data S131 preferably includes determining the positionof the mobile electronic device relative to the vehicle experiencingvehicular travel, but may additionally or alternatively includedetermining the position of the mobile electronic device relative to anyother references (e.g., another person, a building, the earth). Deviceposition relative to the vehicle may help identify a driver status in anumber of ways; for instance, a particular user may always place his orher mobile electronic device in a particular cupholder when driving hisor her primary vehicle. As another example, if a user's mobileelectronic device is in a passenger seat of a vehicle, it is unlikelythat the user is driving the vehicle. Device position relative to otherreferences may also help identify a driver status in a number of ways;for instance, if the device is positioned somewhere in the middle of theAtlantic Ocean, it is unlikely that the user is in a car. As anotherexample, if the user is in close proximity to a large number of otherusers, it is also unlikely that the user is in a car. Collecting deviceposition data S131 preferably includes receiving device position datafrom a sensor of the mobile electronic device (e.g., from a GPS sensor)but may additionally or alternatively include receiving device positiondata from any other suitable source. Collecting device position dataS131 may additionally or alternatively include processing receivedposition data. Device position data and position data of a reference maybe processed to create device position data relative to the reference;for example, GPS data from the mobile electronic device and GPS datafrom a GPS sensor attached to the vehicle may be processed to provide aposition of the mobile electronic device relative to the vehicle. Asanother example, a number of mobile electronic devices may communicatethe signal strengths of all detected devices over Bluetooth to eachother; this data may be processed to determine the position of onemobile electronic device relative to the others.

In a first variation, collecting device position data S131 may includedetecting a beacon signal and processing detected beacon signal data todetermine the position of the mobile electronic device relative to abeacon, set of beacons, or other reference point. The beacon signal ispreferably a signal sent by one or more beacons to allow device positionrelative to the beacons to be established. The signal is preferably aBluetooth signal, but may alternatively be any other suitable signal fordetermining device position; e.g., Wi-Fi, radio, visible light,infrared, sonic, ultrasonic, NFC, RFID. If there are multiple beacons,each beacon may produce identical signals, but they may additionally oralternatively produce distinct signals. Signals from multiple beaconsmay be distinguished by amplitude, duration, frequency, phase, type ofsignal (e.g., sonic vs. electromagnetic), and/or in any other suitableway. Beacons may be connected to each other by wires or may communicatewith each other wirelessly. Beacons may transmit other signals than thebeacon signal (for example, beacons capable of transmitting andreceiving Bluetooth signals may also act as Bluetooth transponders forthe vehicle or other system to be connected to the mobile electronicdevice). Instructions for producing the beacon signal (e.g., the beaconsignal waveform) is preferably stored in the beacons, but additionallyor alternatively may be transmitted to the beacons by the vehicle,mobile electronic device, or any other suitable source. If the beaconsare connected to or in communication with the mobile electronic device,the mobile electronic device preferably has the ability to modify thebeacon signal. For example, the mobile electronic device may reduce theamplitude of a beacon signal if position has been static andaccelerometers in the mobile electronic device have not detectedmovement. As another example, the mobile electronic device may alter thebeacon signal dynamically to confirm or improve position measurements.

Device position relative to the beacons may be established bytriangulation, signal strength measurement, time of flight, and/or anyother suitable method. The beacons are preferably positioned in aparticular way to allow device position relative to the beacons to beprocessed into device position relative to the vehicle. For instance, ifa beacon is placed on the driver's side window of a car, signal strengthof the beacon as measured by the mobile electronic device may becorrelated to a distance from the beacon. If there are four beaconsplaced in different positions (for instance, on each window of a carhaving four windows), signal strength from each beacon may be used todetermine the location of the mobile electronic device in a coordinatesystem determined by the beacons. In an example embodiment of the firstvariation, as shown in FIG. 2, two beacons are mounted or positioned onopposite sides of a vehicle, allowing lateral position of the mobileelectronic device to be determined (e.g., whether the mobile electronicdevice is on the driver or passenger side of the vehicle).

In a second variation, collecting device position data S131 may includesending a beacon signal over the stereo system of a vehicle. The beaconsignal is preferably sent to the stereo system by the mobile electronicdevice, but additionally or alternatively arrive at the stereo system byany suitable method. The beacon signal is preferably a sound or soundsspecifically intended as a beacon signal but may additionally oralternatively be based on a modification to other sound signals (e.g.,modulating music being played over the speakers as a signal). The beaconsignal may also be based on characteristics of the speakers; e.g., theright speaker signal is identified by a characteristic popping noise.The beacon signals played over each channel are preferably different toallow for location relative to each channel's speakers (for example, theright channel and left channel signals played may be different). Themobile electronic device can preferably determine position data from thesignals by comparing the beacon signals recorded by a microphone of themobile electronic device to a reference (such as the beacon signals assent to the vehicle stereo system). Alternatively, the beacon signalsplayed over each channel may be substantially similar in waveform butoffset in phase from one another to create regions of constructive anddestructive interference. The beacon signals are preferably changed overtime (e.g., in frequency, in amplitude, and/or in phase) to move theregions of constructive and destructive interference. The regions ofconstructive and destructive interference are preferably correlated topositions in the car. This correlation may be determined from knowledgeabout the speaker positions (for example, if the vehicle identity isknown, the speaker positions may also be known), estimations of speakerpositions, or calibration data. An example calibration might involveasking a user to hold a phone still in a vehicle while different beaconsignals are transmitted over the speakers while collecting calibrationmeasurements of generated beacon signals. The user preferably is askedto hold the phone in a specific position (e.g., between driver andpassenger seats at ear level), but alternatively may not be asked tohold the phone in a specific position.

In a third variation, collecting device position data S131 may includeecholocation. To collect echolocation data, the mobile electronic devicepreferably sends a signal over a speaker contained within the mobileelectronic device. After sending the signal, the mobile electronicdevice preferably records and analyzes sound using a microphone of themobile electronic device. This sound is then processed; preferably anecho of the signal sent by the mobile electronic device is identified.By comparing the recorded echo to the signal sent, the mobile electronicdevice can preferably determine information about its position. Themobile electronic device preferably can determine device position databy comparing echo characteristics to echo characteristics of knownlocations. Alternatively, the mobile electronic device may simplycorrelate certain echo characteristics to particular users or drivingstatuses, or echo characteristics may be compared to any other suitabledata.

Step S132, which includes collecting device motion data, functions tocollect data on motion of the mobile electronic device. Device motiondata may help identify driver status in a number of ways. In a firstexample, device position data may be inferred from device motion data;whenever a particular user drives, he places his phone in a cupholder,which bounces around in the cupholder with a motion characteristic toboth the phone's position in the cupholder and the user's vehicle motion(discussed in Step S133). In a second example, vehicle motion data maybe inferred from device motion data; if the GPS of a mobile electronicdevice shows the mobile electronic device traveling at 50 miles perhour, it is likely that the major component of the device motion datacaptured by GPS is due to vehicle motion, driver status could then bedetermined from inferred vehicle motion data as in Step S133. In a thirdexample, device motion data may help directly identify driver status; aparticular driver who always carries his phone in his pocket may movehis leg in a characteristic manner (for example, from gas pedal to brakepedal following certain patterns) or may enter a vehicle on the driver'sside in a characteristic manner (e.g. a device user may lean right whenentering the driver's side and may lean left when entering thepassenger's side) and thus move the phone in a substantially similarcharacteristic manner. This characteristic manner may be based on thegait of individuals and the way they handle vehicle doors, the specificvehicles they enter and the side from which they enter the vehicle. Thischaracteristic manner might also be useful in determining vehicleidentity (e.g. the characteristic motion of an individual entering alow-slung sports car is different than the characteristic motion of anindividual entering a minivan). If device motion data is used directly,device motion data may be filtered to highlight or remove suspectedvehicle motion data (for example, a long deceleration might becharacteristic of a car slowing, while a short deceleration might becharacteristic of a leg movement). Additionally or alternatively, devicemotion data may be processed with motion data from another source (e.g.,accelerometer data might be compared with GPS data either from themobile electronic device or from a sensor tied to the vehicle) to createisolated device motion data (i.e., device motion data with contributionsfrom vehicle motion removed). Collecting device motion data S132preferably includes collecting device motion data relative to areference; the reference may be a positional reference (change inposition relative to a reference position over time), an inertialreference (change in velocity relative to a reference velocity), or anyother suitable reference. Alternatively, device motion data may becollected without relation to a reference. Collecting device motion dataS132 preferably includes collecting device motion data from motionsensors (e.g., accelerometers, gyroscopes) of the mobile electronicdevice, but may additionally or alternatively include collecting devicemotion data from any suitable source. Collecting device motion data S132may additionally or alternatively include collecting data on theposition of the mobile electronic device over time and creating devicemotion data from the device position data; device position data ispreferably collected as in Step S131, but may alternatively be collectedin any suitable manner. Collecting device motion data S132 mayadditionally or alternatively include collecting any other data thatcould be used to infer device motion; for example, compass data could becollected over time to determine rotational motion, camera data could beused to determine motion through analysis of captured images over time,and barometer data could be collected over time to determine verticalmotion.

Step S133, which includes collecting vehicle motion data, functions tocollect data on the motion of a vehicle the mobile electronic device isin, connected to, and/or attached to. Collecting vehicle motion datapreferably includes collecting vehicle motion data from sensorsconnected to a vehicle (for example, a built in GPS sensor, or a GPSsensor attached to a vehicle's windshield), but may additionally oralternatively include inferring vehicle motion data from the devicemotion data or collecting vehicle motion data from any other suitablesource. If vehicle motion data is inferred from device motion data, itis preferably isolated from device motion data in a substantiallysimilar way as isolated device motion is produced from device motiondata in Step S132 (although isolated vehicle motion would becomplementary to isolated device motion). Vehicle motion data ispreferably captured in substantially similar manners to device motiondata, but may additionally or alternatively be captured in any suitablemanner. Vehicle motion data may help to identify driver status in anumber of ways; for instance, vehicle motion data may be used to createa driving pattern signature, as shown in FIG. 3.

A driving-pattern signature may be based on one or more signals. Forexample, driving route patterns may be used as a first signal. A userwill typically follow particular routes. Driving along a particularroute may indicate one user is the driver rather than another. Forexample, if two users often drive a family car, but the first userdrives the car to work, and the second driver only drives the car on theweekend, then a travel route to or from work may indicate that the firstdriver is the driver. Style of driving controls may be a second signal.Collecting vehicle motion data may include collecting steering (e.g.,changes in direction), acceleration, and braking data. Such data may beused to differentiate between drivers. In the example above, the firstuser may have an aggressive driving style, and the second user may havea more passive driving style. If the telematic application is sensingthe vehicle experiencing slower speeds, smooth turns, and loweraccelerations, then that may signal that the second user is the driver.

Step S134, which includes collecting vehicle identifying data, functionsto collect data to identify a vehicle as a particular type of vehicle ora particular vehicle. Vehicle identifying data is preferably any datarelating to the identity or type of a vehicle. Vehicle identifying datamay help to determine driver status by leveraging correlations (eithermanually defined or otherwise inferred) between particular drivers andparticular vehicles. For example, if a particular user usually drives aparticular car to work, if the user is in that car during his or hernormal commute time, there is a high likelihood that the user is drivingthe car. In some situations, a remote telematic platform and/or thetelematic application can statistically predict which users are likelythe primary drivers of a vehicle based on who is in the vehicle when thevehicle is driven. Alternatively, a vehicle identity signal may beexplicitly associated with a vehicle.

Collecting vehicle identifying data S134 preferably includes collectingidentifying data for a vehicle containing or linked to the mobileelectronic device, but may additionally or alternatively includecollecting identifying data for any relevant vehicle. Vehicleidentifying data may include characteristic audio data (as shown in FIG.4), characteristic vehicle motion data, signals transmitted by avehicle, beacon identification data (as shown in FIG. 5), and/or anyother suitable data.

Characteristic vehicle audio data preferably includes data that canidentify a vehicle and/or users as shown in FIG. 4. Characteristic audiodata is preferably an audio sampling or a plurality of audio samplingsthat can be used in matching the audio sample to other samples.Vehicles, particularly different models of cars, can have uniqueacoustical properties depending on the engine, sound insulation of thecabin, and other vehicle design properties. Additionally, usage patternsmay impact characteristic audio data. For example, radio preferences(e.g., volume and type of music), phone positioning (e.g., keep phone inpockets, a purse, in a cup holder, on a dock, etc.), conversations, andother factors may impact the audio signature. Thus, Block S134 caninclude implementing one or more machine learning and signal processingalgorithms, described below, configured for matching/identifyingcharacteristic audio data and associating such characteristic audio datawith the vehicle and/or users.

Characteristic vehicle motion data preferably includes vehicle motiondata collected by Step S133 that is characteristic to a particularvehicle, as opposed to a particular driver. For example, it might beapparent from vehicle motion data that a vehicle has anti-lock brakes(from characteristic motion associated with the anti-lock brakes inlow-traction scenarios), this could be used to distinguish the vehiclefrom vehicles without anti-lock brakes. As another example, verticalmovement as measured in vehicle motion data may potentially be relatedto suspension in the vehicle (a vehicle with softer shocks will absorbjolts better) as opposed to a particular driving pattern.

Signals transmitted by a vehicle preferably include Wi-Fi, radio,visible light, infrared, sonic, ultrasonic, NFC, and/or RFID signals.Signals transmitted by a vehicle may additionally or alternativelyinclude electronic signals, e.g., signals transmitted over an ODBIIinterface.

Beacon identification data, as shown in FIG. 5 preferably includes anysignals sent by beacons containing data that could be linked to vehicleidentity, with the beacons as described in Step S131. Additionally oralternatively, beacon identification data may include passive beaconidentification data. For example, the beacon may be a phone dock inwhich a driver places their phone. The structure of the dock may includestructural elements to induce identification of the vehicle. Forexample, the dock may include a bar code, identification number, orother visible identifiers that can be read by the telematic applicationthrough a camera of the device when the device is coupled to the dock.The beacon is preferably uniquely identifiable. As the beacon ispreferably semi-permanently installed within a car (e.g., the beacon isleft in the car over several trips), the beacon may additionally beuniquely associated with one vehicle. Additionally, a single driver canbe associated with the beacon or vehicle. The driver may be explicitlyassociated with the beacon/vehicle, wherein a user registers the beaconin an account profile. Alternatively, the driver may be automaticallyassociated with the beacon/vehicle based on data relating to when theuser is present and the vehicle is being driven.

Step S135, which includes collecting vehicle use data, functions tocollect data on how a vehicle is used. Vehicle use data preferablyincludes data relating to the use of a vehicle aside from vehicle motiondata, but may additionally or alternatively include any data relevant tovehicle use. Vehicle use data may help to determine driver status byleveraging correlations between vehicle use patterns and particulardrivers. For example, a particular user may usually turn on the radio toa particular station when driving, or may always adjust the driver'sseat to a particular position. Vehicle use data is preferably collectedby querying sensors within the vehicle, but alternatively may becollected by sensors in the mobile electronic device or may be collectedin any suitable manner. Vehicle use data preferably includes data on anyvehicle parameters that can be set or modified directly or indirectly byusers; e.g., stereo settings, seat settings, seat sensor data (usuallyintended for airbags, but could be used to detect presence ofpassengers), climate control settings, window use data, door lock data,cruise control data, transmission data (including shifts and timing),windshield wiper data, and headlight data.

Step S136, which includes collecting device use data, functions tocollect data on how the mobile electronic device is used. Device usedata may help to determine driver status by leveraging correlationsbetween device use patterns and driver status. For example, a particularuser may text a lot if he or she is not driving, but may not text at allif he or she is driving. As another example, the telematic applicationmay detect if a user is using other applications or services of thedevice. Such behavior may be used as an indicator that the user is notdriving. Device use data may include data on when user input was lastreceived by the mobile electronic device, user input data, data relatingto application use, internet activity data, phone call activity data,text message activity data, device settings data, and/or any other datarelating to how the mobile electronic device is used.

Step S140, which includes determining driver status, functions to useDSI data to determine the driver status. Driver status preferablyincludes data relating to the driver of a vehicle (e.g., the identity ofthe driver) and/or users of the telematic application. For example,driver status may identify the driver of a vehicle as a known user, aknown driver who is not a known user, or an unknown driver. Driverstatus may additionally or alternatively provide information aboutwhether the user of the mobile electronic device is driving or not.

In one variation, the patterns for the user of the telematic applicationand/or other drivers of a vehicle are collected and characterizedthrough historical DSI data. If collected DSI data do not correspond tothose of the user, then the device is preferably determined to be in apassenger mode (i.e., the user associated with the device is likely notthe driver). If collected DSI data correspond to those of the user, thenthe device may be determined to be in a driver mode (i.e., the userassociated with the device is likely the driver). Collected DSI data mayalso allow the mobile electronic device to determine that while the userof the mobile electronic device is not driving, the driver of a vehicleis another driver known to the telematic application. This other drivermay be a user of the telematic application on another mobile electronicdevice or may simply be a driver known to the telematic applicationthrough collection of DSI data while the user was a passenger.Correlations between DSI data and particular drivers may be storedlocally in the mobile electronic device, may be available to the mobileelectronic device through the internet, or may be available in any othersuitable manner. Storing correlations between DSI data and particulardrivers in the cloud could allow for linked users; for example, allowinga person to collect DSI data for his or her spouse while a passenger.Historical data collected and maintained on a remote telematic platformmay enable not only determining the driver status of the device activelysensing and relaying information, but also the driver status of otherusers that have historical data. For example, within a family, there maybe multiple drivers of a particular car. If it is determined that theuser is likely in the family car, and that a first family member is apassenger of the car, then it may also signal that a second familymember is the driver. This may be accomplished even if the second familymember does not have a device that is actively recording the trip. Forexample, a beacon may identify a device to be in a passenger seat of aparticular car. The identified car may have a second driver (the secondfamily member), to whom the DSI data may correspond.

In another variation, DSI data is compared to predicted patterns forparticular drivers and/or users or to general DSI data indicators.Predicted patterns may be generated from identifying information ofusers and/or drivers (for instance, demographic information; youngermale drivers are more likely to speed than older female drivers), fromhistorical DSI data, and/or from any other suitable source. General DSIdata indicators include information used to identify a driver not basedon a particular user; for instance if a mobile electronic device ispositioned in the driver's seat of a vehicle, it is likely that the userof the mobile electronic device is the driver.

The conclusions indicated from multiple sources of DSI data may beweighted in making a final determination. As with the case of collectingthe driving-pattern signature, the driver status may not be determineduntil the vehicle is in route or has completed travel. Other signals mayafford immediate detection of driver status upon entering the car.However, the DSI data throughout an entire trip or significant portionof a trip may be considered.

Any suitable elements of S150 (and/or other suitable elements of themethod) can be performed by a computing system comprising one or morecomputing subsystems implemented in one or more of: a personal computer,a mobile computing device, a server, a cloud-based computing system,and/or any other computing device. For example, any or all of theseelements can be performed by and/or with one or more decision modules(e.g., as shown in FIGS. 7A-7B), and the method can include providinginstructions in computer code corresponding to any or all of themodules, as described above and below. The modules can use one or moreof: regression, classification, neural networks (e.g., convolutionalneural networks), heuristics, equations (e.g., weighted equations,etc.), selection (e.g., from a library), instance-based methods (e.g.,nearest neighbor), regularization methods (e.g., ridge regression),decision trees, Bayesian methods, kernel methods, probability,deterministics, or any other suitable method. In a specific example, adecision module can determine a score corresponding to each known driverbased on the DSI data (e.g., based on similarity of the DSI data topreviously-collected data associated with the known driver, based onlikelihood of the known driver to generate data similar to the DSI data,etc.), and if one of the scores exceeds a threshold (e.g., constantthreshold, dynamically determined threshold, shared threshold,driver-specific threshold, etc.), the decision module can select thecorresponding known driver (e.g., determine that the driver of thevehicle is the known driver corresponding to that score). In thisspecific example, if multiple scores exceed the threshold, the drivercorresponding to the highest score can be selected. In this specificexample, as additional DSI data is collected, the decision module canupdate the scores based further on the additional DSI data, and canrevise a driver determination (or lack thereof) based on the updatedscores. However, the decision modules can operate in any other suitablemanner.

Step S150, which includes recording the driver status, functions to logtelematic data with the appropriate driver. The driver status ispreferably logged along with telematic data, and the data is preferablytransmitted from the telematic application to the remote telematicplatform. Telematic data is preferably stored for a user if thetelematic application is in a driver mode (i.e., the user of the deviceis predicted to be driving). Telematic data may optionally not bepersistently stored if the telematic application is in a passenger mode.However, passenger data may be used in particular applications and sotelematic data while in a passenger mode may optionally be stored.Additionally, if the driver is determined to be a user other than theone directly associated with the device, the telematic data may beassociated with the determined driver. In some described variations, avehicle identity (or other vehicle identifier) may be determined. Adetermined vehicle identity can additionally be associated with storedtelematic data. Telematic data that is confidently associated with aparticular driver can be used to more accurately evaluate the driverquality of various users, which may have particular applicability tocompanies providing vehicle insurance.

2. Systems for Determining a Driver in a Telematic Application

As shown in FIG. 6, a system for determining a driver in a telematicapplication functions to detect if the operating device is in a drivingmode or a passenger mode through at least a telematic application. Themethods of determining driving status may be performed through severalvarious approaches as are described herein. The system may additionallybe configured in various alternative embodiments to support the processof detecting a driver. The techniques of determining a driver may relyupon car-based devices, audio detection, and/or physical eventdetection. The system may additionally include a remote telematicplatform that can be communicatively coupled to the telematicapplication to facilitate in managing and/or processing data accordingto any one or more algorithms associated with the method 100 describedabove.

The telematic application functions to primarily coordinate thecollection of telematic data and determination of driver status. Thetelematics application is preferably programmed in computer code andexecutes at an associated user device upon installation of thetelematics application onto the user device. An instance of thetelematic application is preferably associated with a user identity oraccount. Preferably, a user signs in with account credentials into theapplication. The telematic application is preferably operable on amobile device. The mobile device is preferably a mobile phone, but mayalternatively be a wearable computing device, a tablet, a personaldata-logging device, or any suitable device. The telematic deviceapplication is preferably an application downloaded and installed on thedevice, but the application may alternatively be embedded in the deviceor installed on the device in any suitable manner. The telematic deviceapplication may at least partially operate in the background, but thetelematic application may additionally include a user-facing interface.Telematic data and history data may be viewed from the user interface.Additionally, the user interface may be used to explicitly receiveconfirmation of if the primary user is a driver or a passenger. Thebackground operation of the telematic device application preferablyfunctions to detect and record vehicle data. The telematic deviceapplication may additionally interface with services provided by theoperating system or other frameworks to efficiently monitor and collecttelematic data.

The telematic device application can preferably provide data on locationand routes, movements, driving patterns (e.g., steering and brakingcharacteristics), and other properties. The telematic device applicationpreferably includes interfaces to services and sensors of the devicesuch as GPS sensors, location services, accelerometers, gyroscopes,presence sensors, and/or any suitable input signal accessible by theapplication. The telematic data may be used with outside data sources tocorrelate additional properties of driving. The additional properties ofdriving may be generated on the telematic device application oralternatively by the remote telematic data platform.

The remote telematic platform functions to host, process, and sharedata. The remote telematic platform is preferably a multitenant platformthat is used by multiple instances of the telematic device application.The remote telematic platform preferably includes an account system anda telematic data storage system to store driving log data. The drivinglog data is preferably stored in association with a driver. The drivinglog data may additionally or alternatively include parameters forvehicle identity and passengers. The telematic device applicationpreferably periodically syncs collected data with the remote telematicplatform. The remote telematic platform is preferably an internetaccessible platform that may be implemented on a computer cluster, adistributed computing environment, a dedicated server, or any suitablehosting architecture.

In one preferred embodiment, the system may include at least one beacon,which functions to be a signal to the telematic application. In onevariation, the beacon is an active beacon that transmits some signalthat is received by the telematic application. The active beacon maytransmit a signal to facilitate determining the distance between thebeacon and the device. The beacon may use any suitable range findingsensing technique such as using time of flight distance measurements,signal strength, or other suitable techniques. The system mayadditionally include two beacons to facilitate triangulation. The activebeacon may alternatively or additionally transmit a signal to facilitatein communicating an identity code associated with the token. A beaconmay use light signals (e.g., infrared), ultrasound, Bluetooth, Wifi,NFC, RFID, and/or other suitable mediums when transmitting to thetelematic application on the device. The beacon may alternatively be apassive device that functions as an identifier for the telematicapplication. The beacon is preferably a physical device that can beplaced, mounted, affixed, inserted, or otherwise coupled to a vehicle.

In another preferred embodiment, the system may include an audioprofiling engine. The audio profiling engine is preferably a moduleconfigured for performing audio collection, characterizing audio, andmatching signatures. The audio profiling engine preferably uses amicrophone of the device to collect audio input. The audio input issampled and converted into signatures that can be algorithmicallymatched.

In a variation of the preferred embodiment, the telematic applicationmay send a notification to the user when active usage is detected duringvehicular travel. The notification can serve as a reminder to notoperate the device while driving and also to receive explicitconfirmation that the user is a passenger.

The system and methods of the preferred embodiment and variationsthereof can be embodied and/or implemented at least in part as a machineconfigured to receive a computer-readable medium storingcomputer-readable instructions. The instructions are preferably executedby computer-executable components preferably integrated with thetelematic device application and the remote telematic platform. Thecomputer-readable medium can be stored on any suitable computer-readablemedia such as RAMs, ROMs, flash memory, EEPROMs, optical devices (CD orDVD), hard drives, floppy drives, or any suitable device. Thecomputer-executable component is preferably a general or applicationspecific processor, but any suitable dedicated hardware orhardware/firmware combination device can alternatively or additionallyexecute the instructions.

As a person skilled in the art will recognize from the previous detaileddescription and from the figures and claims, modifications and changescan be made to the preferred embodiments of the invention withoutdeparting from the scope of this invention defined in the followingclaims.

I claim:
 1. A method for driver identification comprising: sampling avehicle motion dataset during a time period corresponding to movement ofa vehicle using at least one of an accelerometer and a GPS sensor of auser device arranged within the vehicle; extracting a vehicular motionsignature from the vehicle motion dataset during the time period;determining a vehicle identifier of the vehicle based on a comparisonbetween the vehicular motion signature, a characteristic vehicle motion,and movement of the user device as a user enters the vehicle that isdetermined using accelerometer data and GPS sensor data from the userdevice; and based on the vehicle identifier and the vehicle motiondataset, determining an identity of a driver operating the vehiclethroughout the time period.
 2. The method of claim 1, wherein extractingthe vehicular motion signature comprises extracting an accelerationpattern during the time period, and wherein the characteristic vehiclemotion comprises an average acceleration rate of the vehicle.
 3. Themethod of claim 1, wherein extracting the vehicular motion signaturecomprises extracting a braking pattern during the time period, andwherein the characteristic vehicle motion comprises an anti-lock brakingpattern.
 4. The method of claim 1, wherein extracting the vehicularmotion signature comprises a vibration pattern during the time period,and wherein the characteristic vehicle motion comprises a suspensionresponse pattern.
 5. The method of claim 1, wherein extracting thevehicular motion signature comprises extracting a driving route, andwherein the characteristic vehicle motion comprises a driving routepattern.
 6. The method of claim 1, wherein the vehicle motion signaturecomprises a combination of steering behavior, acceleration behavior, andbraking behavior during the time period, and further comprisingdetermining the identity of the driver based on the combination ofsteering behavior, acceleration behavior, and braking behavior.
 7. Themethod of claim 1, wherein the user device is movably coupled to thevehicle through an article of clothing of the driver, wherein the driveris coupled to the vehicle by a seatbelt.
 8. The method of claim 1,further comprising sampling audio data at a microphone of the userdevice; and determining the identity of the driver based further on theaudio data.
 9. The method of claim 1, further comprising determining arelative position of the user device with respect to the vehicle, anddetermining the identity of the driver based further on the relativeposition.
 10. The method of claim 9, wherein determining the relativeposition comprises: at the user device, sampling a set of beacon signaldata; and determining the relative position based on the set of beaconsignal data.
 11. A method for driver identification comprising: at auser device arranged in a vehicle, determining a relative position ofthe user device with respect to the vehicle during a time periodcorresponding to vehicular travel; based on the relative position of theuser device with respect to the vehicle, determining a vehicleidentifier of the vehicle; sampling a motion dataset during the timeperiod using at least one of an accelerometer and a GPS sensor of theuser device; and based on the vehicle identifier and the motion dataset,determining an identity of a driver operating the vehicle throughout thetime period.
 12. The method of claim 11, further comprising removablycoupling the user device to the vehicle through a mount fixed to thevehicle.
 13. The method of claim 11, further comprising sampling audiodata at a microphone of the user device.
 14. The method of claim 13,wherein the audio data is emitted by the vehicle; and further comprisingdetermining the vehicle identifier based on the set of audio data. 15.The method of claim 14, further comprising extracting an acousticproperty of the vehicle from the audio data, and determining the vehicleidentifier based on the acoustic property.
 16. The method of claim 13,wherein the identity of the driver is determined based further on theaudio data.
 17. The method of claim 13, further comprising determiningthe relative position based on the audio data.
 18. The method of claim11, wherein determining the relative position comprises: at the userdevice, sampling a set of beacon signal data; and determining therelative position based on the set of beacon signal data.
 19. The methodof claim 11, further comprising collecting vehicle use data during thetime period, and determining the identity of the driver based on thevehicle use data.
 20. The method of claim 19, wherein the vehicle usedata comprises a climate control setting determined by a vehicleoccupant during the time period.